The Low Noise Limit in Gene Expression

PLOS ONE, Dec 2019

Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i) the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii) the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can–and in the case of E. coli does–control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1) a global noise floor uniformly imposed on all genes by expression bursting; and (2) high noise distributed to only a select group of genes.

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The Low Noise Limit in Gene Expression

October The Low Noise Limit in Gene Expression Roy D. Dar 0 1 2 Brandon S. Razooky 0 1 2 Leor S. Weinberger 0 1 2 Chris D. Cox 0 1 2 Michael L. Simpson 0 1 2 0 1 Gladstone Institute of Virology and Immunology , San Francisco , California, United States of America, 2 Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 3 Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America, 4 Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America, 5 Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, Tennessee, United States of America, 6 Laboratory of Immune Cell Epigenetics and Signaling, The Rockefeller University , New York , New York, United States of America, 7 QB3: California Institute for Quantitative Biosciences, University of California San Francisco , San Francisco , California, United States of America, 8 Department of Biochemistry and Biophysics, University of California San Francisco , San Francisco , California, United States of America, 9 Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Tennessee, United States of America, 10 Department of Materials Science and Engineering, University of Tennessee , Knoxville, Tennessee , United States of America 1 Funding: RDD was supported by an NIH NRSA fellowship (AI104380) and K22 (AI120746). BSR and MLS were supported by the Collective Phenomena in Nanophases Research Theme at the Center for Nanophase Materials Sciences, which is sponsored at Oak Ridge National Laboratory by the Office of Basic Energy Sciences, U.S. Department of Energy. BSR was supported in part by funds from a Merck Postdoctoral Fellowship at The Rockefeller University. LSW acknowledges support from the Pew Scholars Program in the Biomedical Sciences, the W. M. Keck Foundation Research Excellence Award , the 2 Editor: Lev Tsimring, University of California San Diego, UNITED STATES Protein noise measurements are increasingly used to elucidate biophysical parameters. Unfortunately noise analyses are often at odds with directly measured parameters. Here we show that these inconsistencies arise from two problematic analytical choices: (i) the assumption that protein translation rate is invariant for different proteins of different abundances, which has inadvertently led to (ii) the assumption that a large constitutive extrinsic noise sets the low noise limit in gene expression. While growing evidence suggests that transcriptional bursting may set the low noise limit, variability in translational bursting has been largely ignored. We show that genome-wide systematic variation in translational efficiency can-and in the case of E. coli does-control the low noise limit in gene expression. Therefore constitutive extrinsic noise is small and only plays a role in the absence of a systematic variation in translational efficiency. These results show the existence of two distinct expression noise patterns: (1) a global noise floor uniformly imposed on all genes by expression bursting; and (2) high noise distributed to only a select group of genes. - In principle the structure of noise in protein populations can be used to infer the architecture and dynamics of the underlying gene circuits and networks [1, 2]. However, inference is indirect, requires trust in analytical models, and may require reliance on assumptions. Despite the indirect approach, these analytical models have demonstrated some qualitative successes, but undoubtedly suffer from quantitative problems. A particularly relevant example from contemporary research is transcriptional bursting (Fig 1A); a model of transcription where multiple Competing Interests: The authors have declared that no competing interests exist. Fig 1. Assumptions of extrinsic noise coupling reveal a disparity in inferred versus actual transcriptional burst size measurements. (A) Transcriptional bursting (red dashed box) occurs when a promoter stochastically switches between an ‘OFF’, G0 state, and ‘ON’, G1 state, at rates kOFF and kON. In the G1 state mRNA, M, is transcribed at rate α, and translated into protein, P, at rate kp. mRNA and protein decay at rates γm and γp respectively. Constitutive expression (blue dashed box) is made of the processes of transcription from the G1 state, translation, and decay of M and P. Extrinsic noise, i.e. global fluctuations in shared resources, can potentially affect transcriptional bursting, constitutive expression, or both. (B) Schematic representation of promoter transitioning as a square wave where the average timing between bursts, TOFF, is 1/ kON. The average duration of a burst, TON, i.e. time in the ON, G1 state, is 1/ kOFF. The average number of bursts over a length of time is termed the transcriptional burst frequency. (C) Measured transcription (...truncated)


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Roy D. Dar, Brandon S. Razooky, Leor S. Weinberger, Chris D. Cox, Michael L. Simpson. The Low Noise Limit in Gene Expression, PLOS ONE, 2015, Volume 10, Issue 10, DOI: 10.1371/journal.pone.0140969